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Found 2,760 Skills
Verify that a change really works before you claim completion
Apply Lean Startup methodology — Build-Measure-Learn loop, MVP, validated learning, and pivot decisions. Use this skill when the user is launching a new product or startup and needs to validate ideas quickly, design an MVP, decide whether to pivot or persevere, or reduce wasted effort on unvalidated assumptions — even if they say 'should we build this', 'how do we test this idea', 'when should we pivot', or 'we're burning cash with no traction'.
Create distinctive brands that customers choose because they believe there's no substitute, using Marty Neumeier's Brand Gap and Zag frameworks Use when: **Building a new brand** from scratch (startup, product, service); **Repositioning an existing brand** that's become commoditized; **Defining brand differentiation** when competitors all look the same; **Creating brand guidelines** for consistent execution; **Evaluating brand strength** through structured testing
Runs the Metabase semantic checker against a tree of Representation Format YAML files to verify that all references resolve — cross-entity references (collection_id, dashboard_id, parent_id, parameter source cards, snippet references, transform tags, etc.) and references to columns inside MBQL and native queries. Use when the user asks to "semantic check", "check references", "validate queries against the schema", or diagnose a broken reference. Requires database metadata on disk (by default `.metabase/metadata.json`).
Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.
Check BIM model consistency: naming conventions, parameter completeness, spatial relationships, and data integrity across model elements.
Use when creating or editing any prompt (commands, hooks, skills, subagent instructions) to verify it produces desired behavior - applies RED-GREEN-REFACTOR cycle to prompt engineering using subagents for isolated testing
Audit whether an ML or AI paper's experimental baselines are necessary, fair, current, and reviewer-proof. Use this skill whenever the user is planning experiments, comparing methods, choosing baselines, worried about missing SOTA or unfair comparisons, preparing a reviewer-proof experiment section, or converting a literature review into must-have, should-have, optional, and not-comparable baselines.
[Hyper] Analyze bugs, present repair options, then implement and verify the user-selected fix path. Routes simple bugs directly; tracks complex multi-phase investigations via .hypercore/bug-fix/ JSON flow.
Validates practitioner credentials and license status against the NPI registry. Cross-references specialties, credentials, and practice addresses against official records. Returns Verified / Partially Verified / Unverified / Flagged per practitioner with mismatch details and source URLs. Triggers: "verify these doctors", "check provider credentials", "validate licenses", "verify NPI numbers", "cross-check credentials against NPI", "compliance audit on providers", "are these practitioners still licensed", "validate my provider list". Accepts CSV, Google Sheet URL, or pasted data. Do NOT use for extracting providers from practice URLs — use healthcare-providers-extract instead. Do NOT use for filling data gaps — use healthcare-providers-enrich instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.
Manage .facts files — atomic, validatable truth statements about a project. Install, check, list, add, edit, remove, and lint facts via the CLI. ALWAYS read this skill when the user mentions facts in any capacity.
Use when given a GitHub issue URL or number to investigate and implement a fix. Triggers on "fix issue", "fix bug", "fix